Cost-Sensitive Boosting Algorithm for Classifying Underdeveloped Regions in Indonesia

Bayu Suseno (IPB University)
Bagus Sartono (Department of Statistics, Faculty of Mathematics and Natural Sciences, IPB University)
Khairil Anwar Notodiputro (Department of Statistics, Faculty of Mathematics and Natural Sciences, IPB University)

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Vol. 2023 No. 1 (2023): Proceedings of 2023 International Conference on Data Science and Official St

Imbalanced classes are indicated by having more instances of some classes than others. The cost-sensitive boosting algorithm is a modification of the AdaBoost algorithm, which aims to solve the problem of imbalanced classes. In this study, we evaluate the cost-sensitive Boosting algorithm AdaC2 using Indonesia's underdeveloped region's data. This study confirms that the cost-sensitive boosting algorithm (AdaC2) performs better in classifying the instances in the minority classes than standard classifiers algorithms.